To reduce carbon emissions,clean energy is being integrated into the power system.Wind power is connected to the grid in a distributed form,but its high variability poses a challenge to grid stability.This article com...To reduce carbon emissions,clean energy is being integrated into the power system.Wind power is connected to the grid in a distributed form,but its high variability poses a challenge to grid stability.This article combines wind turbine monitoring data with numerical weather prediction(NWP)data to create a suitable wind power prediction framework for distributed grids.First,high-precision NWP of the turbine range is achieved using weather research and forecasting models(WRF),and Kriging interpolation locates predicted meteorological data at the turbine site.Then,a preliminary predicted power series is obtained based on the fan’s wind speed-power conversion curve,and historical power is reconstructed using variational mode decomposition(VMD)filtering to form input variables in chronological order.Finally,input variables of a single turbine enter the temporal convolutional network(TCN)to complete initial feature extraction,and then integrate the outputs of all TCN layers using Long Short Term Memory Networks(LSTM)to obtain power prediction sequences for all turbine positions.The proposed method was tested on a wind farm connected to a distributed power grid,and the results showed it to be superior to existing typical methods.展开更多
The intelligent operation management of distribution services is crucial for the stability of power systems.Integrating the large language model(LLM)with 6G edge intelligence provides customized management solutions.H...The intelligent operation management of distribution services is crucial for the stability of power systems.Integrating the large language model(LLM)with 6G edge intelligence provides customized management solutions.However,the adverse effects of false data injection(FDI)attacks on the performance of LLMs cannot be overlooked.Therefore,we propose an FDI attack detection and LLM-assisted resource allocation algorithm for 6G edge intelligenceempowered distribution power grids.First,we formulate a resource allocation optimization problem.The objective is to minimize the weighted sum of the global loss function and total LLM fine-tuning delay under constraints of long-term privacy entropy and energy consumption.Then,we decouple it based on virtual queues.We utilize an LLM-assisted deep Q network(DQN)to learn the resource allocation strategy and design an FDI attack detection mechanism to ensure that fine-tuning remains on the correct path.Simulations demonstrate that the proposed algorithm has excellent performance in convergence,delay,and security.展开更多
There is instability in the distributed energy storage cloud group end region on the power grid side.In order to avoid large-scale fluctuating charging and discharging in the power grid environment and make the capaci...There is instability in the distributed energy storage cloud group end region on the power grid side.In order to avoid large-scale fluctuating charging and discharging in the power grid environment and make the capacitor components showa continuous and stable charging and discharging state,a hierarchical time-sharing configuration algorithm of distributed energy storage cloud group end region on the power grid side based on multi-scale and multi feature convolution neural network is proposed.Firstly,a voltage stability analysis model based onmulti-scale and multi feature convolution neural network is constructed,and the multi-scale and multi feature convolution neural network is optimized based on Self-OrganizingMaps(SOM)algorithm to analyze the voltage stability of the cloud group end region of distributed energy storage on the grid side under the framework of credibility.According to the optimal scheduling objectives and network size,the distributed robust optimal configuration control model is solved under the framework of coordinated optimal scheduling at multiple time scales;Finally,the time series characteristics of regional power grid load and distributed generation are analyzed.According to the regional hierarchical time-sharing configuration model of“cloud”,“group”and“end”layer,the grid side distributed energy storage cloud group end regional hierarchical time-sharing configuration algorithm is realized.The experimental results show that after applying this algorithm,the best grid side distributed energy storage configuration scheme can be determined,and the stability of grid side distributed energy storage cloud group end region layered timesharing configuration can be improved.展开更多
False data injection attack(FDIA)is an attack that affects the stability of grid cyber-physical system(GCPS)by evading the detecting mechanism of bad data.Existing FDIA detection methods usually employ complex neural ...False data injection attack(FDIA)is an attack that affects the stability of grid cyber-physical system(GCPS)by evading the detecting mechanism of bad data.Existing FDIA detection methods usually employ complex neural networkmodels to detect FDIA attacks.However,they overlook the fact that FDIA attack samples at public-private network edges are extremely sparse,making it difficult for neural network models to obtain sufficient samples to construct a robust detection model.To address this problem,this paper designs an efficient sample generative adversarial model of FDIA attack in public-private network edge,which can effectively bypass the detectionmodel to threaten the power grid system.A generative adversarial network(GAN)framework is first constructed by combining residual networks(ResNet)with fully connected networks(FCN).Then,a sparse adversarial learning model is built by integrating the time-aligned data and normal data,which is used to learn the distribution characteristics between normal data and attack data through iterative confrontation.Furthermore,we introduce a Gaussian hybrid distributionmatrix by aggregating the network structure of attack data characteristics and normal data characteristics,which can connect and calculate FDIA data with normal characteristics.Finally,efficient FDIA attack samples can be sequentially generated through interactive adversarial learning.Extensive simulation experiments are conducted with IEEE 14-bus and IEEE 118-bus system data,and the results demonstrate that the generated attack samples of the proposed model can present superior performance compared to state-of-the-art models in terms of attack strength,robustness,and covert capability.展开更多
We describe a specific approach to capacity man a ge ment for distribution grids. Based on simulations, it has been found that by curtailing a maximum of 5% of the yearly energy production on a per-generator basis, di...We describe a specific approach to capacity man a ge ment for distribution grids. Based on simulations, it has been found that by curtailing a maximum of 5% of the yearly energy production on a per-generator basis, distribution grid connection capacity can be doubled. We also present the setting and fi rst results of a fi eld test for validating the approach in a rural distribution grid in northern Germany.展开更多
To adapt to the uncertainty of new energy,increase new energy consumption,and reduce carbon emissions,a high-voltage distribution network energy storage planning model based on robustness-oriented planning and distrib...To adapt to the uncertainty of new energy,increase new energy consumption,and reduce carbon emissions,a high-voltage distribution network energy storage planning model based on robustness-oriented planning and distributed new energy consumption is proposed.Firstly,the spatio-temporal correlation of large-scale wind-photovoltaic energy is modeled based on the Vine Copula model,and the spatial correlation of the generated wind-photovoltaic power generation is corrected to get the spatio-temporal correlation of wind-photovoltaic power generation scenarios.Finally,considering the subsequent development of new energy on demand for high-voltage distribution network peaking margin and the economy of the system peaking,we propose the optimization model of high-voltage distribution network energy storage plant siting and capacity setting for source-storage cooperative peaking.The simulation results show that the proposed energy storage plant planning method can effectively alleviate the branch circuit blockage,promote new energy consumption,reduce the burden of the main grid peak shifting,and leave sufficient peak shifting margin for the subsequent development of a new energy distribution network while ensuring the economy.展开更多
With the growing deployment of smart distribution grid,it has become urgent to investigate the smart distribution grid behavior during transient faults and improve the system stability.The feasibility of segmenting la...With the growing deployment of smart distribution grid,it has become urgent to investigate the smart distribution grid behavior during transient faults and improve the system stability.The feasibility of segmenting large power grids and multiple smart distribution grids interconnections using energy storage technology for improving the system dynamic stability was studied.The segmentation validity of the large power grids and smart distribution grid inverter output interconnections power system using energy storage technology was proved in terms of theoretical analysis.Then,the influences of the energy storage device location and capacity on the proposed method were discussed in detail.The conclusion is obtained that the ESD optimal locations are allocated at the tie line terminal buses in the interconnected grid,respectively.The effectiveness of the proposed method was verified by simulations in an actual power system.展开更多
The charging of electric vehicles(EVs) impacts the distribution grid, and its cost depends on the price of electricity when charging. An aggregator that is responsible for a large fleet of EVs can use a market-based c...The charging of electric vehicles(EVs) impacts the distribution grid, and its cost depends on the price of electricity when charging. An aggregator that is responsible for a large fleet of EVs can use a market-based control algorithm to coordinate the charging of these vehicles, in order to minimize the costs. In such an optimization, the operational parameters of the distribution grid, to which the EVs are connected, are not considered. This can lead to violations of the technical constraints of the grid(e.g., undervoltage, phase unbalances); for example, because many vehicles start charging simultaneously when the price is low. An optimization that simultaneously takes the economic and technical aspects into account is complex, because it has to combine time-driven control at the market level with eventdriven control at the operational level. Diff erent case studies investigate under which circumstances the market-based control, which coordinates EV charging, conflicts with the operational constraints of the distribution grid. Especially in weak grids, phase unbalance and voltage issues arise with a high share of EVs. A low-level voltage droop controller at the charging point of the EV can be used to avoid many grid constraint violations, by reducing the charge power if the local voltage is too low. While this action implies a deviation from the cost-optimal operating point, it is shown that this has a very limited impact on the business case of an aggregator, and is able to comply with the technical distribution grid constraints, even in weak distribution grids with many EVs.展开更多
The importance of computational grids in hydraulic numerical models is studied by numerical simulation of jet flow in a rectangular duct which is linked with a fixed width inlet and a different width outlet using a st...The importance of computational grids in hydraulic numerical models is studied by numerical simulation of jet flow in a rectangular duct which is linked with a fixed width inlet and a different width outlet using a standard k-epsilon turbulence model. The computational results show the numerical solutions may not be reasonable because of the incorrect computational grid and each numerical model bass grid-independent solution. The computational grid has a definitive effect on the accuracy and stability of the computational solution, which must be divided well according to the simulated geometry and physical characters of hydraulic problems. The main guidelines about the formation of computational grid in such aspects as node distribution, smoothness and skewness of grid, have been given.展开更多
Smart distribution grid needs data communication systems as a support to complete their important functions. The smart distribution grid of the data and information are increasingly adopting internet protocol and Ethe...Smart distribution grid needs data communication systems as a support to complete their important functions. The smart distribution grid of the data and information are increasingly adopting internet protocol and Ethernet technology. The IP addresses are more and more important for the smart distribution grid equipment. The current IPv4 protocol occupies a dominant position; therefore, the challenges of the evolution to IPv6 and network security are faced by data communication systems of the smart distribution grid. The importance of data communications network and its main bearer of business were described. The data communications network from IPv4 to IPv6 evolution of the five processes and four stages of the transition were analyzed. The smart distribution grid data communications network security and types of their offensive and defensive were discussed. And the data communications network security architecture was established. It covers three dimensions, the security level, the communications network security engineering and the communications network security management. The security architecture safeguards the evolution to IPv6 for the smart distribution grid data communication systems.展开更多
A distribution grid is generally characterized by a high R/X （resistance/reactance） ratio and it is radial in nature. By design, a distribution grid system is not an active network, and it is normally designed in su...A distribution grid is generally characterized by a high R/X （resistance/reactance） ratio and it is radial in nature. By design, a distribution grid system is not an active network, and it is normally designed in such a way that power flows from transmission system via distribution system to consumers. But in a situation when wind turbines are connected to the distribution grid, the power source will change from one source to two sources, in this case, network is said to be active. This may probably have an impact on the distribution grid to whenever the wind turbine is connected. The best way to know the impact of wind turbine on the distribution grid in question is by carrying out load flow analysis on that system with and without the connection of wind turbines. Two major fundamental calculations： the steady-state voltage variation at the PCC （point of common coupling） and the calculation of short-circuit power of the grid system at the POC （point of connection） are necessary before carrying out the load flow study on the distribution grid. This paper, therefore, considers these pre-load flow calculations that are necessary before carrying out load flow study on the test distribution grid. These calculations are carded out on a test distribution system.展开更多
The increasing use of renewable energy in the power system results in strong stochastic disturbances and degrades the control performance of the distributed power grids.In this paper,a novel multi-agent collaborative ...The increasing use of renewable energy in the power system results in strong stochastic disturbances and degrades the control performance of the distributed power grids.In this paper,a novel multi-agent collaborative reinforcement learning algorithm is proposed with automatic optimization,namely,Dyna-DQL,to quickly achieve an optimal coordination solution for the multi-area distributed power grids.The proposed Dyna framework is combined with double Q-learning to collect and store the environmental samples.This can iteratively update the agents through buffer replay and real-time data.Thus the environmental data can be fully used to enhance the learning speed of the agents.This mitigates the negative impact of heavy stochastic disturbances caused by the integration of renewable energy on the control performance.Simulations are conducted on two different models to validate the effectiveness of the proposed algorithm.The results demonstrate that the proposed Dyna-DQL algorithm exhibits superior stability and robustness compared to other reinforcement learning algorithms.展开更多
Most ground faults in distribution network are caused by insulation deterioration of power equipment.It is difficult to find the insulation deterioration of the distribution network in time,and the development trend o...Most ground faults in distribution network are caused by insulation deterioration of power equipment.It is difficult to find the insulation deterioration of the distribution network in time,and the development trend of the initial insulation fault is unknown,which brings difficulties to the distribution inspection.In order to solve the above problems,a situational awareness method of the initial insulation fault of the distribution network based on a multi-feature index comprehensive evaluation is proposed.Firstly,the insulation situation evaluation index is selected by analyzing the insulation fault mechanism of the distribution network,and the relational database of the distribution network is designed based on the data and numerical characteristics of the existing distribution management system.Secondly,considering all kinds of fault factors of the distribution network and the influence of the power supply region,the evaluation method of the initial insulation fault situation of the distribution network is proposed,and the development situation of the distribution network insulation fault is classified according to the evaluation method.Then,principal component analysis was used to reduce the dimension of the training samples and test samples of the distribution network data,and the support vector machine(SVM)was trained.The optimal parameter combination of the SVM model was found by the grid search method,and a multi-class SVM model based on 1-v-1 method was constructed.Finally,the trained multi-class SVM was used to predict 6 kinds of situation level prediction samples.The results of simulation examples show that the average prediction accuracy of 6 situation levels is above 95%,and the perception accuracy of 4 situation levels is above 96%.In addition,the insulation maintenance decision scheme under different situation levels is able to be given when no fault occurs or the insulation fault is in the early stage,which can meet the needs of power distribution and inspection for accurately sensing the insulation fault situation.The correctness and effectiveness of this method are verified.展开更多
Although power grids have become safer with increased situational awareness,major extreme events still pose reliability and resilience challenges,primarily at the distribution level,due to increased vulnerabilities an...Although power grids have become safer with increased situational awareness,major extreme events still pose reliability and resilience challenges,primarily at the distribution level,due to increased vulnerabilities and limited recovery resources.Information and communication technologies(ICTs)have introduced new vulnerabilities that have been widely investigated in previous studies.These vulnerabilities include remote device failures,communication channel disturbances,and cyberattacks.However,only few studies have explored the opportunity offered by communications to improve the resilience of power grids and eliminate the notion that power-telecom interdependencies always pose a threat.This paper proposes a communication-aware restoration approach of smart distribution grids,which leverages power-telecom interdependencies to determine the optimal restoration strategies.The states of grid-energized telecom points are tracked to provide the best restoration actions,which are enabled through the resilience resources of repair,manual switching,remote reconfiguration,and distributed generators.As the telecom network coordinates the allocation of these resilience resources based on their coupling tendencies,different telecom architectures have been introduced to investigate the contribution of private and public ICTs to grid management and restoration operations.System restoration uses the configuration that follows a remote fast response as the input to formulate the problem as mixed-integer linear programming.Results from numerical simulations reveal an enhanced restoration process derived from telecom-aware recovery and the co-optimization of resilience resources.The existing disparity between overhead and underground power line configurations is also quantified.展开更多
Grid-connected converters(GPC)are playing an increasingly important role in distribution networks.Performing electromagnetic transient(EMT)simulations on power electronics and distribution networks can significantly i...Grid-connected converters(GPC)are playing an increasingly important role in distribution networks.Performing electromagnetic transient(EMT)simulations on power electronics and distribution networks can significantly improve the analysis accuracy.However,the existing simulation softwarestruggles to handle distribution networks with a large number of power electronic switches,leading to unacceptable simulation times.To address this issue,a system-hierarchical multi-rate co-simulation framework is proposed.The system is hierarchically divided into different rate subsystems based on timescales,and solvers withdifferent simulation rates are used to solve them separately.A Taylor-series-based variable-step solver is proposed for power electronic systems,and numerical compensation algorithms are designed for multi-rate interfaces to improve the system stabilityand accuracy.Compared with commercial software,the proposed framework increased the simulation speed by more than 200 times in the studied case,involving 576 switching devices and 14 bus distribution networks,while contributing less than 1%to the relativeerror.展开更多
Solid-state transformer-based smart transformer(ST)can provide the dc connectivity and advanced services to improve the grid performance and to increase the penetration of the power electronics interfaced resources(e....Solid-state transformer-based smart transformer(ST)can provide the dc connectivity and advanced services to improve the grid performance and to increase the penetration of the power electronics interfaced resources(e.g.,distributed generators and electric vehicle charging stations)in modern electricity distribution grids.Since the ST is a new and effective paradigm of the electricity grid evolution to well understand the ST,this paper systematically presents the basic architecture and the typical control schemes of the ST and then the advanced services that ST can provide to improve the electricity grids performances in terms of the power flow control,power quality improvement,active damping and active contribution to improve distribution grid resilience by means of enabling autonomous microgrids operation as well as launching a restoration procedure following a general blackout.展开更多
Based on the background of achieving carbon peaking and carbon neutrality, the development and application of new high-power compressors, electric grid drilling RIGS and electric fracturing pump system provide new equ...Based on the background of achieving carbon peaking and carbon neutrality, the development and application of new high-power compressors, electric grid drilling RIGS and electric fracturing pump system provide new equipment support for the electric, green and intelligent development of shale gas fields in China. However, the harmonic pollution of shale gas grid becomes more serious due to the converter and frequency conversion device in the system, which easily causes harmonic resonance problem. Therefore, the harmonic resonance of shale gas grid is comprehensively analyzed and treated. Firstly, the working mechanism of compressor, electric drilling RIGS of the harmonic impedance model of electric fracturing pump system is established. Secondly, the main research methods of harmonic resonance analysis are introduced, and the basic principle of modal analysis is explained. Modal analysis method was used to analyze. Finally, harmonic resonance is suppressed. The results show that there may be multiple resonant frequency points in the distribution network changes, but these changes are relatively clear;if the original resonant frequency point of the resonant loop does not exist, the resonant frequency point disappears. The optimal configuration strategy of passive filter can effectively suppress harmonic resonance of distribution network in shale gas field.展开更多
Distribution grid topology and admittance information are essential for system planning,operation,and protection.In many distribution grids,missing or inaccurate topology and admittance data call for efficient estimat...Distribution grid topology and admittance information are essential for system planning,operation,and protection.In many distribution grids,missing or inaccurate topology and admittance data call for efficient estimation methods.However,measurement data may be insufficient or contaminated with large noise,which will fundamentally limit the estimation accuracy.This work explores the theoretical precision limits of the topology and admittance estimation(TAE)problem with different measurement devices,noise levels,and numbers of measurements.On this basis,we propose a conservative progressive self-adaptive(CPS)algorithm to estimate the topology and admittance.The results on IEEE 33 and 141-bus systems validate that the proposed CPS method can approach the theoretical precision limits under various measurement settings.展开更多
As the communication needs in the smart distribution grid continue to rise,using existing resources to meet this growing demand poses a significant challenge.This paper researches on spectrum allocation strategies uti...As the communication needs in the smart distribution grid continue to rise,using existing resources to meet this growing demand poses a significant challenge.This paper researches on spectrum allocation strategies utilizing cognitive radio(CR)technology.We consider a model containing strong time-sensitive and regular communication service requirements such as distribution terminal communication services,which can be seen as a user with primary data(PD)and weak time-sensitive services such as power quality monitoring,which can be seen as a user with secondary data(SD).To fit the diversity of services in smart distribution grids(SDGs),we formulate an optimization problem with two indicators,including the sum of SD transmission rates and the maximum latency of them.Then,we analyze the two convex sub-problems and utilize convex optimization methods to obtain the optimal power and frequency bandwidth allocation for the users with SD.The simulation results indicate that,when the available transmission power of SD is low,Maximization of Transmission Sum Rate(MTSR)achieves lower maximum transmit time.Conversely,when the available transmission power is high,the performance of Minimization of the Maximum Latency(MML)is better,compared with MTSR.展开更多
This paper presents a practical method for calculating a power user’s customer interruption costs(CIC)under specific conditions.This novel method has been developed,based on the CIC results predicted by Lawrence Berk...This paper presents a practical method for calculating a power user’s customer interruption costs(CIC)under specific conditions.This novel method has been developed,based on the CIC results predicted by Lawrence Berkeley National Laboratory(LBNL),so that the key factors,such as customer type,customer size,interruption occurrence time and interruption duration can be considered.As compared to the LBNL method,the method proposed here is easy to understand and easy to execute with an acceptable error.It lays a solid foundation for further investigation of distributed generators and demand response in assessing reliability value of smart distribution grid(SDG).The effectiveness of the proposed method is confirmed through the assessment of RBTS-Bus2.展开更多
基金funded by National Key Research and Development Program of China (2021YFB2601400)。
文摘To reduce carbon emissions,clean energy is being integrated into the power system.Wind power is connected to the grid in a distributed form,but its high variability poses a challenge to grid stability.This article combines wind turbine monitoring data with numerical weather prediction(NWP)data to create a suitable wind power prediction framework for distributed grids.First,high-precision NWP of the turbine range is achieved using weather research and forecasting models(WRF),and Kriging interpolation locates predicted meteorological data at the turbine site.Then,a preliminary predicted power series is obtained based on the fan’s wind speed-power conversion curve,and historical power is reconstructed using variational mode decomposition(VMD)filtering to form input variables in chronological order.Finally,input variables of a single turbine enter the temporal convolutional network(TCN)to complete initial feature extraction,and then integrate the outputs of all TCN layers using Long Short Term Memory Networks(LSTM)to obtain power prediction sequences for all turbine positions.The proposed method was tested on a wind farm connected to a distributed power grid,and the results showed it to be superior to existing typical methods.
基金supported by the Science and Technology Project of State Grid Corporation of China under Grant Number 52094021N010(5400-202199534A-0-5-ZN).
文摘The intelligent operation management of distribution services is crucial for the stability of power systems.Integrating the large language model(LLM)with 6G edge intelligence provides customized management solutions.However,the adverse effects of false data injection(FDI)attacks on the performance of LLMs cannot be overlooked.Therefore,we propose an FDI attack detection and LLM-assisted resource allocation algorithm for 6G edge intelligenceempowered distribution power grids.First,we formulate a resource allocation optimization problem.The objective is to minimize the weighted sum of the global loss function and total LLM fine-tuning delay under constraints of long-term privacy entropy and energy consumption.Then,we decouple it based on virtual queues.We utilize an LLM-assisted deep Q network(DQN)to learn the resource allocation strategy and design an FDI attack detection mechanism to ensure that fine-tuning remains on the correct path.Simulations demonstrate that the proposed algorithm has excellent performance in convergence,delay,and security.
基金supported by State Grid Corporation Limited Science and Technology Project Funding(Contract No.SGCQSQ00YJJS2200380).
文摘There is instability in the distributed energy storage cloud group end region on the power grid side.In order to avoid large-scale fluctuating charging and discharging in the power grid environment and make the capacitor components showa continuous and stable charging and discharging state,a hierarchical time-sharing configuration algorithm of distributed energy storage cloud group end region on the power grid side based on multi-scale and multi feature convolution neural network is proposed.Firstly,a voltage stability analysis model based onmulti-scale and multi feature convolution neural network is constructed,and the multi-scale and multi feature convolution neural network is optimized based on Self-OrganizingMaps(SOM)algorithm to analyze the voltage stability of the cloud group end region of distributed energy storage on the grid side under the framework of credibility.According to the optimal scheduling objectives and network size,the distributed robust optimal configuration control model is solved under the framework of coordinated optimal scheduling at multiple time scales;Finally,the time series characteristics of regional power grid load and distributed generation are analyzed.According to the regional hierarchical time-sharing configuration model of“cloud”,“group”and“end”layer,the grid side distributed energy storage cloud group end regional hierarchical time-sharing configuration algorithm is realized.The experimental results show that after applying this algorithm,the best grid side distributed energy storage configuration scheme can be determined,and the stability of grid side distributed energy storage cloud group end region layered timesharing configuration can be improved.
基金supported in part by the the Natural Science Foundation of Shanghai(20ZR1421600)Research Fund of Guangxi Key Lab of Multi-Source Information Mining&Security(MIMS21-M-02).
文摘False data injection attack(FDIA)is an attack that affects the stability of grid cyber-physical system(GCPS)by evading the detecting mechanism of bad data.Existing FDIA detection methods usually employ complex neural networkmodels to detect FDIA attacks.However,they overlook the fact that FDIA attack samples at public-private network edges are extremely sparse,making it difficult for neural network models to obtain sufficient samples to construct a robust detection model.To address this problem,this paper designs an efficient sample generative adversarial model of FDIA attack in public-private network edge,which can effectively bypass the detectionmodel to threaten the power grid system.A generative adversarial network(GAN)framework is first constructed by combining residual networks(ResNet)with fully connected networks(FCN).Then,a sparse adversarial learning model is built by integrating the time-aligned data and normal data,which is used to learn the distribution characteristics between normal data and attack data through iterative confrontation.Furthermore,we introduce a Gaussian hybrid distributionmatrix by aggregating the network structure of attack data characteristics and normal data characteristics,which can connect and calculate FDIA data with normal characteristics.Finally,efficient FDIA attack samples can be sequentially generated through interactive adversarial learning.Extensive simulation experiments are conducted with IEEE 14-bus and IEEE 118-bus system data,and the results demonstrate that the generated attack samples of the proposed model can present superior performance compared to state-of-the-art models in terms of attack strength,robustness,and covert capability.
文摘We describe a specific approach to capacity man a ge ment for distribution grids. Based on simulations, it has been found that by curtailing a maximum of 5% of the yearly energy production on a per-generator basis, distribution grid connection capacity can be doubled. We also present the setting and fi rst results of a fi eld test for validating the approach in a rural distribution grid in northern Germany.
基金supported by State Grid Anhui Electric Power Co.,Ltd.Research Program(B3120923000C).
文摘To adapt to the uncertainty of new energy,increase new energy consumption,and reduce carbon emissions,a high-voltage distribution network energy storage planning model based on robustness-oriented planning and distributed new energy consumption is proposed.Firstly,the spatio-temporal correlation of large-scale wind-photovoltaic energy is modeled based on the Vine Copula model,and the spatial correlation of the generated wind-photovoltaic power generation is corrected to get the spatio-temporal correlation of wind-photovoltaic power generation scenarios.Finally,considering the subsequent development of new energy on demand for high-voltage distribution network peaking margin and the economy of the system peaking,we propose the optimization model of high-voltage distribution network energy storage plant siting and capacity setting for source-storage cooperative peaking.The simulation results show that the proposed energy storage plant planning method can effectively alleviate the branch circuit blockage,promote new energy consumption,reduce the burden of the main grid peak shifting,and leave sufficient peak shifting margin for the subsequent development of a new energy distribution network while ensuring the economy.
基金Project(N110404031)supported by the Fundamental Research Funds for the Central Universities,China
文摘With the growing deployment of smart distribution grid,it has become urgent to investigate the smart distribution grid behavior during transient faults and improve the system stability.The feasibility of segmenting large power grids and multiple smart distribution grids interconnections using energy storage technology for improving the system dynamic stability was studied.The segmentation validity of the large power grids and smart distribution grid inverter output interconnections power system using energy storage technology was proved in terms of theoretical analysis.Then,the influences of the energy storage device location and capacity on the proposed method were discussed in detail.The conclusion is obtained that the ESD optimal locations are allocated at the tie line terminal buses in the interconnected grid,respectively.The effectiveness of the proposed method was verified by simulations in an actual power system.
基金supported in part by the European Commission through the project P2P-Smartest:Peer to Peer Smart Energy Distribution Networks (H2020-LCE-2014-3,project 646469)
文摘The charging of electric vehicles(EVs) impacts the distribution grid, and its cost depends on the price of electricity when charging. An aggregator that is responsible for a large fleet of EVs can use a market-based control algorithm to coordinate the charging of these vehicles, in order to minimize the costs. In such an optimization, the operational parameters of the distribution grid, to which the EVs are connected, are not considered. This can lead to violations of the technical constraints of the grid(e.g., undervoltage, phase unbalances); for example, because many vehicles start charging simultaneously when the price is low. An optimization that simultaneously takes the economic and technical aspects into account is complex, because it has to combine time-driven control at the market level with eventdriven control at the operational level. Diff erent case studies investigate under which circumstances the market-based control, which coordinates EV charging, conflicts with the operational constraints of the distribution grid. Especially in weak grids, phase unbalance and voltage issues arise with a high share of EVs. A low-level voltage droop controller at the charging point of the EV can be used to avoid many grid constraint violations, by reducing the charge power if the local voltage is too low. While this action implies a deviation from the cost-optimal operating point, it is shown that this has a very limited impact on the business case of an aggregator, and is able to comply with the technical distribution grid constraints, even in weak distribution grids with many EVs.
文摘The importance of computational grids in hydraulic numerical models is studied by numerical simulation of jet flow in a rectangular duct which is linked with a fixed width inlet and a different width outlet using a standard k-epsilon turbulence model. The computational results show the numerical solutions may not be reasonable because of the incorrect computational grid and each numerical model bass grid-independent solution. The computational grid has a definitive effect on the accuracy and stability of the computational solution, which must be divided well according to the simulated geometry and physical characters of hydraulic problems. The main guidelines about the formation of computational grid in such aspects as node distribution, smoothness and skewness of grid, have been given.
文摘Smart distribution grid needs data communication systems as a support to complete their important functions. The smart distribution grid of the data and information are increasingly adopting internet protocol and Ethernet technology. The IP addresses are more and more important for the smart distribution grid equipment. The current IPv4 protocol occupies a dominant position; therefore, the challenges of the evolution to IPv6 and network security are faced by data communication systems of the smart distribution grid. The importance of data communications network and its main bearer of business were described. The data communications network from IPv4 to IPv6 evolution of the five processes and four stages of the transition were analyzed. The smart distribution grid data communications network security and types of their offensive and defensive were discussed. And the data communications network security architecture was established. It covers three dimensions, the security level, the communications network security engineering and the communications network security management. The security architecture safeguards the evolution to IPv6 for the smart distribution grid data communication systems.
文摘A distribution grid is generally characterized by a high R/X （resistance/reactance） ratio and it is radial in nature. By design, a distribution grid system is not an active network, and it is normally designed in such a way that power flows from transmission system via distribution system to consumers. But in a situation when wind turbines are connected to the distribution grid, the power source will change from one source to two sources, in this case, network is said to be active. This may probably have an impact on the distribution grid to whenever the wind turbine is connected. The best way to know the impact of wind turbine on the distribution grid in question is by carrying out load flow analysis on that system with and without the connection of wind turbines. Two major fundamental calculations： the steady-state voltage variation at the PCC （point of common coupling） and the calculation of short-circuit power of the grid system at the POC （point of connection） are necessary before carrying out the load flow study on the distribution grid. This paper, therefore, considers these pre-load flow calculations that are necessary before carrying out load flow study on the test distribution grid. These calculations are carded out on a test distribution system.
基金supported by the National Natural Sci-ence Foundation of China(No.52277108)Guangdong Provincial Department of Science and Technology(No.2022A0505020015).
文摘The increasing use of renewable energy in the power system results in strong stochastic disturbances and degrades the control performance of the distributed power grids.In this paper,a novel multi-agent collaborative reinforcement learning algorithm is proposed with automatic optimization,namely,Dyna-DQL,to quickly achieve an optimal coordination solution for the multi-area distributed power grids.The proposed Dyna framework is combined with double Q-learning to collect and store the environmental samples.This can iteratively update the agents through buffer replay and real-time data.Thus the environmental data can be fully used to enhance the learning speed of the agents.This mitigates the negative impact of heavy stochastic disturbances caused by the integration of renewable energy on the control performance.Simulations are conducted on two different models to validate the effectiveness of the proposed algorithm.The results demonstrate that the proposed Dyna-DQL algorithm exhibits superior stability and robustness compared to other reinforcement learning algorithms.
基金funded by the Science and Technology Project of China Southern Power Grid(YNKJXM20210175)the National Natural Science Foundation of China(52177070).
文摘Most ground faults in distribution network are caused by insulation deterioration of power equipment.It is difficult to find the insulation deterioration of the distribution network in time,and the development trend of the initial insulation fault is unknown,which brings difficulties to the distribution inspection.In order to solve the above problems,a situational awareness method of the initial insulation fault of the distribution network based on a multi-feature index comprehensive evaluation is proposed.Firstly,the insulation situation evaluation index is selected by analyzing the insulation fault mechanism of the distribution network,and the relational database of the distribution network is designed based on the data and numerical characteristics of the existing distribution management system.Secondly,considering all kinds of fault factors of the distribution network and the influence of the power supply region,the evaluation method of the initial insulation fault situation of the distribution network is proposed,and the development situation of the distribution network insulation fault is classified according to the evaluation method.Then,principal component analysis was used to reduce the dimension of the training samples and test samples of the distribution network data,and the support vector machine(SVM)was trained.The optimal parameter combination of the SVM model was found by the grid search method,and a multi-class SVM model based on 1-v-1 method was constructed.Finally,the trained multi-class SVM was used to predict 6 kinds of situation level prediction samples.The results of simulation examples show that the average prediction accuracy of 6 situation levels is above 95%,and the perception accuracy of 4 situation levels is above 96%.In addition,the insulation maintenance decision scheme under different situation levels is able to be given when no fault occurs or the insulation fault is in the early stage,which can meet the needs of power distribution and inspection for accurately sensing the insulation fault situation.The correctness and effectiveness of this method are verified.
基金supported by EDF/Orange/SNCF in the framework of the Chair on Risk and Resilience of Complex Systems(CentraleSupelec,EDF,Orange,SNCF).
文摘Although power grids have become safer with increased situational awareness,major extreme events still pose reliability and resilience challenges,primarily at the distribution level,due to increased vulnerabilities and limited recovery resources.Information and communication technologies(ICTs)have introduced new vulnerabilities that have been widely investigated in previous studies.These vulnerabilities include remote device failures,communication channel disturbances,and cyberattacks.However,only few studies have explored the opportunity offered by communications to improve the resilience of power grids and eliminate the notion that power-telecom interdependencies always pose a threat.This paper proposes a communication-aware restoration approach of smart distribution grids,which leverages power-telecom interdependencies to determine the optimal restoration strategies.The states of grid-energized telecom points are tracked to provide the best restoration actions,which are enabled through the resilience resources of repair,manual switching,remote reconfiguration,and distributed generators.As the telecom network coordinates the allocation of these resilience resources based on their coupling tendencies,different telecom architectures have been introduced to investigate the contribution of private and public ICTs to grid management and restoration operations.System restoration uses the configuration that follows a remote fast response as the input to formulate the problem as mixed-integer linear programming.Results from numerical simulations reveal an enhanced restoration process derived from telecom-aware recovery and the co-optimization of resilience resources.The existing disparity between overhead and underground power line configurations is also quantified.
基金Supported by the National Key Research and Development Program(2023YFB3307000).
文摘Grid-connected converters(GPC)are playing an increasingly important role in distribution networks.Performing electromagnetic transient(EMT)simulations on power electronics and distribution networks can significantly improve the analysis accuracy.However,the existing simulation softwarestruggles to handle distribution networks with a large number of power electronic switches,leading to unacceptable simulation times.To address this issue,a system-hierarchical multi-rate co-simulation framework is proposed.The system is hierarchically divided into different rate subsystems based on timescales,and solvers withdifferent simulation rates are used to solve them separately.A Taylor-series-based variable-step solver is proposed for power electronic systems,and numerical compensation algorithms are designed for multi-rate interfaces to improve the system stabilityand accuracy.Compared with commercial software,the proposed framework increased the simulation speed by more than 200 times in the studied case,involving 576 switching devices and 14 bus distribution networks,while contributing less than 1%to the relativeerror.
基金the German Federal Ministry of Education and Research(BMBF)within the Kopernikus Project ENSURE"New ENergy grid StructURes for the German Energiewende"(03SFK1I0-2)。
文摘Solid-state transformer-based smart transformer(ST)can provide the dc connectivity and advanced services to improve the grid performance and to increase the penetration of the power electronics interfaced resources(e.g.,distributed generators and electric vehicle charging stations)in modern electricity distribution grids.Since the ST is a new and effective paradigm of the electricity grid evolution to well understand the ST,this paper systematically presents the basic architecture and the typical control schemes of the ST and then the advanced services that ST can provide to improve the electricity grids performances in terms of the power flow control,power quality improvement,active damping and active contribution to improve distribution grid resilience by means of enabling autonomous microgrids operation as well as launching a restoration procedure following a general blackout.
文摘Based on the background of achieving carbon peaking and carbon neutrality, the development and application of new high-power compressors, electric grid drilling RIGS and electric fracturing pump system provide new equipment support for the electric, green and intelligent development of shale gas fields in China. However, the harmonic pollution of shale gas grid becomes more serious due to the converter and frequency conversion device in the system, which easily causes harmonic resonance problem. Therefore, the harmonic resonance of shale gas grid is comprehensively analyzed and treated. Firstly, the working mechanism of compressor, electric drilling RIGS of the harmonic impedance model of electric fracturing pump system is established. Secondly, the main research methods of harmonic resonance analysis are introduced, and the basic principle of modal analysis is explained. Modal analysis method was used to analyze. Finally, harmonic resonance is suppressed. The results show that there may be multiple resonant frequency points in the distribution network changes, but these changes are relatively clear;if the original resonant frequency point of the resonant loop does not exist, the resonant frequency point disappears. The optimal configuration strategy of passive filter can effectively suppress harmonic resonance of distribution network in shale gas field.
基金funded by the Science and Technology Project of State Grid Corporation of China(5100-202199519A-0-5-ZN).
文摘Distribution grid topology and admittance information are essential for system planning,operation,and protection.In many distribution grids,missing or inaccurate topology and admittance data call for efficient estimation methods.However,measurement data may be insufficient or contaminated with large noise,which will fundamentally limit the estimation accuracy.This work explores the theoretical precision limits of the topology and admittance estimation(TAE)problem with different measurement devices,noise levels,and numbers of measurements.On this basis,we propose a conservative progressive self-adaptive(CPS)algorithm to estimate the topology and admittance.The results on IEEE 33 and 141-bus systems validate that the proposed CPS method can approach the theoretical precision limits under various measurement settings.
基金supported in part by the Fundamental Research Funds for the Central Universities(2023JBZX029)the National Natural Science Foundation of China(61931001 and 62202035)the S&T Program of Hebei,China(SZX2020034)。
文摘As the communication needs in the smart distribution grid continue to rise,using existing resources to meet this growing demand poses a significant challenge.This paper researches on spectrum allocation strategies utilizing cognitive radio(CR)technology.We consider a model containing strong time-sensitive and regular communication service requirements such as distribution terminal communication services,which can be seen as a user with primary data(PD)and weak time-sensitive services such as power quality monitoring,which can be seen as a user with secondary data(SD).To fit the diversity of services in smart distribution grids(SDGs),we formulate an optimization problem with two indicators,including the sum of SD transmission rates and the maximum latency of them.Then,we analyze the two convex sub-problems and utilize convex optimization methods to obtain the optimal power and frequency bandwidth allocation for the users with SD.The simulation results indicate that,when the available transmission power of SD is low,Maximization of Transmission Sum Rate(MTSR)achieves lower maximum transmit time.Conversely,when the available transmission power is high,the performance of Minimization of the Maximum Latency(MML)is better,compared with MTSR.
文摘This paper presents a practical method for calculating a power user’s customer interruption costs(CIC)under specific conditions.This novel method has been developed,based on the CIC results predicted by Lawrence Berkeley National Laboratory(LBNL),so that the key factors,such as customer type,customer size,interruption occurrence time and interruption duration can be considered.As compared to the LBNL method,the method proposed here is easy to understand and easy to execute with an acceptable error.It lays a solid foundation for further investigation of distributed generators and demand response in assessing reliability value of smart distribution grid(SDG).The effectiveness of the proposed method is confirmed through the assessment of RBTS-Bus2.
